It is important to anticipate the management of research data in order to facilitate the various stages in the life of the data. This is one of the objectives of the data management plan.

Don’t think of a data management plan as another administrative burden, but rather as a tool to help you plan your project.

In particular, thinking about a DMP helps to answer some very practical questions:

  • What data will be produced/processed during the project?
  • How large will it be?
  • Will there be few large files or many small ones?
  • What types of data and in what formats will it be stored?
  • How will it be shared between the various project members?
  • Where will it be stored and backed up?
  • What processing and analysis will be required?
  • What infrastructures will be used?

One practical point is to establish guidelines for organizing data within the project.

Another essential point is agreeing on the file format to ensure the project runs smoothly and to facilitate reusing the data later (as part of the project, for a follow-up, or as open data).

The cost of data management can be anticipated in the short and long term. This aspect can be included in an application for ANR-type funding. There are several tools that can be used to assess these costs.

  • Data Management costing tool from the University of Delft is a checklist that shows possible costs at different stages of the data lifecycle, such as collection and cleansing. It is based on the guide proposed by the UK Data Service.. It is based on the guide proposed by the UK Data Service.
  • EPFL Library Cost Calculator for Data Management : this calculation tool takes into account infrastructure costs (storage server, electronic laboratory notebooks, databases, data warehouses, long-term archiving, etc.) over the entire duration of the project.

As early as the project setup phase and during the drafting of the detailed proposal, the guide Incorporating open science into ANR projects: a practical guide published by the GTSO (Open Science Working Group) Data from Couperin, makes it easier to incorporate data management into the project.

The UGA recommends that data management plans (DMPs) have to be created for all research projects, especially doctoral students’ thesis projects. The institution requires this for all projects it funds.

According to the Law on Scientific Integrity (Article 6), institutions “shall define a policy for the conservation, communication, and reuse of the raw results of scientific work.” They must also ensure that their staff implement data management plans.

In this context, the Cellule Data Grenoble Alpes provides personalized support from the project setup stage. They work closely with the project engineering service unit and the HAL UGA team.